Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Qwen3.5 397B is clearly ahead on the aggregate, 71 to 43. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4o mini is also the more expensive model on tokens at $0.15 input / $0.60 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.5 397B. That is roughly Infinityx on output cost alone.
Pick Qwen3.5 397B if you want the stronger benchmark profile. GPT-4o mini only becomes the better choice if coding is the priority.
Qwen3.5 397B
67.7
GPT-4o mini
82
Qwen3.5 397B
52
GPT-4o mini
87.2
Qwen3.5 397B
82
GPT-4o mini
87
Qwen3.5 397B is ahead overall, 71 to 43. The biggest single separator in this matchup is HumanEval, where the scores are 75 and 87.2.
GPT-4o mini has the edge for knowledge tasks in this comparison, averaging 82 versus 67.7. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for coding in this comparison, averaging 87.2 versus 52. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for multilingual tasks in this comparison, averaging 87 versus 82. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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